Analysis of the mirror neuron system for evaluation of stimulus

ABSTRACT

The human mirror neuron system includes neurons that fire both when an individual performs an action and when the individual observes the action being performed by another. Neuro-response data involving the mirror neuron system is collected as a subject is exposed to stimulus material. The stimulus material may include individuals performing actions such as making a purchase, accepting an offer, participating in an activity, etc. Neuro-response data involving the mirror neuron system of the subject is analyzed to determine the propensity of the subject to act.

CROSS REFERENCE TO RELATED APPLICATIONS

This patent is related to U.S. patent application Ser. No. 12/056,190;U.S. patent application Ser. No. 12/056,211; U.S. patent applicationSer. No. 12/056,221; U.S. patent application Ser. No. 12/056,225; U.S.patent application Ser. No. 12/113,863; U.S. patent application Ser. No.12/113,870; U.S. patent application Ser. No. 12/122,240; U.S. patentapplication Ser. No. 12/122,253; U.S. patent application Ser. No.12/122,262; U.S. patent application Ser. No. 12/135,066; U.S. patentapplication Ser. No. 12/135,074; U.S. patent application Ser. No.12/182,851; U.S. patent application Ser. No. 12/182,874; U.S. patentapplication Ser. No. 12/199,557; U.S. patent application Ser. No.12/199,583; U.S. patent application Ser. No. 12/199,596; U.S. patentapplication Ser. No. 12/200,813; U.S. patent application Ser. No.12/234,372; U.S. patent application Ser. No. 12/135,069; U.S. patentapplication Ser. No. 12/234,388; U.S. patent application Ser. No.12/544,921; U.S. patent application Ser. No. 12/544,934; U.S. patentapplication Ser. No. 12/546,586; U.S. patent application Ser. No.12/544,958; U.S. patent application Ser. No. 12/846,242; U.S. patentapplication Ser. No. 12/410,380; U.S. patent application Ser. No.12/410,372; U.S. patent application Ser. No. 12/413,297; U.S. patentapplication Ser. No. 12/608,660; U.S. patent application Ser. No.12/608,685; U.S. patent application Ser. No. 13/444,149; U.S. patentapplication Ser. No. 12/608,696; U.S. patent application Ser. No.12/731,868; U.S. patent application Ser. No. 13/045,457; U.S. patentapplication Ser. No. 12/778,810; U.S. patent application Ser. No.12/778,828; U.S. patent application Ser. No. 13/104,821; U.S. patentapplication Ser. No. 13/104,840; U.S. patent application Ser. No.12/853,197; U.S. patent application Ser. No. 12/884,034; U.S. patentapplication Ser. No. 12/868,531; U.S. patent application Ser. No.12/913,102; U.S. patent application Ser. No. 12/853,213; and U.S. patentapplication Ser. No. 13/105,774.

TECHNICAL FIELD

The present disclosure relates to analyzing the mirror neuron system forevaluation of stimulus materials.

DESCRIPTION OF RELATED ART

Conventional systems for evaluating stimulus materials such as programs,advertising, text, images, video, audio, scents, tastes, materials,offers, and games are usually limited to survey and focus group basedreview. However, conventional systems are subject to semantic,syntactic, metaphorical, cultural, and interpretive errors that preventaccurate and repeatable evaluation.

Consequently, it is desirable to provide improved methods and apparatusfor evaluating stimulus materials.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure may best be understood by reference to the followingdescription taken in conjunction with the accompanying drawings, whichillustrate particular example embodiments.

FIG. 1 illustrates one example of a system for performing mirror neuronsystem analysis using neuro-response data.

FIG. 2 illustrates examples of stimulus attributes that can be includedin a repository.

FIG. 3 illustrates examples of data models that can be used with amirror neuron system analyzer.

FIG. 4 illustrates one example of a query that can be used with themirror neuron system analyzer

FIG. 5 illustrates one example of a report generated using a mirrorneuron system analyzer.

FIG. 6 illustrates one example of a technique for performing mirrorneuron system analysis.

FIG. 7 illustrates one example of technique for performing mirror neuronsystem analysis.

FIG. 8 provides one example of a system that can be used to implementone or more mechanisms.

DESCRIPTION OF PARTICULAR EMBODIMENTS

Reference will now be made in detail to some specific examples of theinvention including the best modes contemplated by the inventors forcarrying out the invention. Examples of these specific embodiments areillustrated in the accompanying drawings. While the invention isdescribed in conjunction with these specific embodiments, it will beunderstood that it is not intended to limit the invention to thedescribed embodiments. On the contrary, it is intended to coveralternatives, modifications, and equivalents as may be included withinthe spirit and scope of the invention as defined by the appended claims.

For example, the techniques and mechanisms of the present invention willbe described in the context of particular types of stimulus. However, itshould be noted that the techniques and mechanisms of the presentinvention apply to a variety of different types of stimulus. In thefollowing description, numerous specific details are set forth in orderto provide a thorough understanding of the present invention. Particularexample embodiments of the present invention may be implemented withoutsome or all of these specific details. In other instances, well knownprocess operations have not been described in detail in order not tounnecessarily obscure the present invention.

Various techniques and mechanisms of the present invention willsometimes be described in singular form for clarity. However, it shouldbe noted that some embodiments include multiple iterations of atechnique or multiple instantiations of a mechanism unless notedotherwise. For example, a system uses a processor in a variety ofcontexts. However, it will be appreciated that a system can use multipleprocessors while remaining within the scope of the present inventionunless otherwise noted. Furthermore, the techniques and mechanisms ofthe present invention will sometimes describe a connection between twoentities. It should be noted that a connection between two entities doesnot necessarily mean a direct, unimpeded connection, as a variety ofother entities may reside between the two entities. For example, aprocessor may be connected to memory, but it will be appreciated that avariety of bridges and controllers may reside between the processor andmemory. Consequently, a connection does not necessarily mean a direct,unimpeded connection unless otherwise noted.

Overview

The human mirror neuron system includes neurons that fire both when anindividual performs an action and when the individual observes theaction being performed by another. Neuro-response data involving themirror neuron system is collected as a subject is exposed to stimulusmaterial. The stimulus material may include individuals performingactions such as making a purchase, accepting an offer, participating inan activity, etc. Neuro-response data involving the mirror neuron systemof the subject is analyzed to determine the propensity of the subject toact.

Example Embodiments

Neurons in the mirror neuron system are cells associated with thepremotor cortex, a portion of the brain involved with planning,selection, and execution of actions. Neurons in the mirror neuron systemhave been observed in humans in the inferior frontal lobe and theposterior parietal lobe. These neurons are active both when anindividual is performing an action and when the individual observesanother performing the action. Some mirror neurons are believed to beactive when activity is performed by another in peripersonal space andnot when activity is performed by another in extrapersonal space. Othershave noted that mirror neuron activity increases as the likelihood ofinteraction with the other individual performing the action increases.It is recognized that mirror neuron activity is particularly pronouncedin the left hemisphere and in women.

Some scientists speculate that the mirror neuron system providesindividuals with the ability experience an action performed by anotheras though the experience was their own. The mirror neuron system may beimportant in allowing individuals to imitate, learn, acquire language,show empathy, and understand others.

The techniques and mechanisms of the present invention recognize thatthe mirror neuron system can also be used to determine the propensity ofan individual to perform an observed activity. According to variousembodiments, an instruction series on how to use a fire extinguisher canbe improved by analyzing mirror neuron system activity for subjectsexposed to the instruction series. An advertisement showing anindividual obtaining and using a product may be evaluated by analyzingmirror neuron system activity for subjects exposed to the advertisement.In some embodiments, a propensity to reach or obtain can be determined.A tourism video depicting an individual travelling to another countrycan be evaluated by analyzing mirror neuron system activity forpotential tourists watching the video.

It is recognized that mu rhythms, having a frequency between 8-13 hertz,decrease when an individual performs an action or observes an actionbeing performed by another. That is, mu rhythms decrease as mirrorneuron activity increases. The techniques and mechanisms of the presentinvention further recognize that gamma rhythms increase as mirror neuronactivity increases. According to various embodiments, mirror neuronsystem activity is measured using a ratio including gamma and/or mu. Inparticular embodiments, mirror neuron system activity is measured usinga ratio including gamma and beta, which includes mu. In some examples,large gamma over mu or gamma over beta values indicate a high propensityto reach, obtain, or imitate. A propensity to reach, obtain, or imitateis referred to herein as a propensity to act. In particular embodiments,a propensity to act index is determined by measuring mirror neuronsystem activity when a subject is exposed to stimulus material having ahuman-like entity such as a human hand performing an action. Howhuman-like the entity has to be may depend on the individual. Someindividuals may have a mirror neuron system that is active whenparticular animals perform activities. Otherwise may have a mirrorneuron system that is active when a computer animation of an individualis observed. A large gamma over mu or gamma over beta value alsoindicates that stimulus material may be effective.

It is recognized that various individuals, groups, and subgroups mayhave more pronounced mirror neuron system responses to stimulusmaterial. In particular embodiments, women typically have significantlyhigher mirror neuron system responses than men. Consequently, apropensity to act index may be calibrated based on demographic groupsuch as gender. According to various embodiments, neuro-response data iscombined with survey responses and resulting behavior information togenerate a propensity to reach index, a learning index, and an empathyindex as well. In some examples, mirror neuron system patternsassociated with particularly effective learning, high levels of empathy,or strong purchase desires are maintained in a mirror neuron systemanalysis repository. Stimulus materials that elicit similar mirrorneuron system patterns for the same individuals, groups, or subgroupsmay be given higher propensity to reach indices, learning indices, orempathy indices.

Mirror neuron system activity can be measured by monitoring activity inregions associated with mirror neurons, such as the posterior parietallobe and the inferior frontal lobe. In some examples, mirror neuronsystem activity can be measured using central nervous system measuressuch as Functional Magnetic Resonance Imaging (fMRI),Electroencephalography (EEG), Magnetoencephlography (MEG), and OpticalImaging. According to various embodiments, these central nervous systemmeasures can be supplemented with other data including autonomic nervoussystem and effector measurements. In particular embodiments, a typicalmirror neuron system exhibits a drop in mu rhythms and/or beta rhythmswhen an individual either acts or observes another person acting.According to various embodiments, the techniques and mechanisms of thepresent invention also measure the increase in gamma rhythms. Thetechniques and mechanisms of the present invention recognize that gammarhythms increase when an individual acts or observes another acting.

Mechanisms for measuring mirror neuron system activity include centralnervous system measurement mechanisms. Some examples of central nervoussystem measurement mechanisms include Functional Magnetic ResonanceImaging (fMRI), Electroencephalography (EEG), Magnetoencephlography(MEG), and Optical Imaging. Optical imaging can be used to measure theabsorption or scattering of light related to concentration of chemicalsin the brain or neurons associated with neuronal firing. MEG measuresmagnetic fields produced by electrical activity in the brain. fMRImeasures blood oxygenation in the brain that correlates with increasedneural activity. However, current implementations of fMRI have poortemporal resolution of few seconds. EEG measures electrical activityassociated with post synaptic currents occurring in the millisecondsrange. Subcranial EEG can measure electrical activity with the mostaccuracy, as the bone and dermal layers weaken transmission of a widerange of frequencies. Nonetheless, surface EEG provides a wealth ofelectrophysiological information if analyzed properly. Even portable EEGwith dry electrodes provides a large amount of neuro-responseinformation. Although the effect of stimulus materials on mirror neuronscan be measured using central nervous system measurement mechanisms, thetechniques and mechanisms of the present invention contemplate usingother mechanisms to further validate the effectiveness of stimulusmaterials. For example, autonomic nervous system and effector measurescan also be used.

Autonomic nervous system measurement mechanisms includeElectrocardiograms (EKG), pupillary dilation, etc. Effector measurementmechanisms include Electrooculography (EOG), eye tracking, facialemotion encoding, reaction time etc.

According to various embodiments, the techniques and mechanisms of thepresent invention intelligently blend multiple modes and manifestationsof precognitive neural signatures with cognitive neural signatures andpost cognitive neurophysiological manifestations to more accuratelyperform mirror neuron system analysis. In some examples, autonomicnervous system measures are themselves used to validate central nervoussystem measures. Effector and behavior responses are blended andcombined with other measures. According to various embodiments, centralnervous system, autonomic nervous system, and effector systemmeasurements are aggregated into a measurement that allows mirror neuronsystem analysis.

In particular embodiments, subjects are exposed to stimulus material anddata such as central nervous system, autonomic nervous system, andeffector data is collected during exposure. According to variousembodiments, data is collected in order to determine a resonance measurethat aggregates multiple component measures that assess resonance data.In particular embodiments, specific event related potential (ERP)analyses and/or event related power spectral perturbations (ERPSPs) areevaluated for different regions of the brain both before a subject isexposed to stimulus and each time after the subject is exposed tostimulus.

According to various embodiments, pre-stimulus and post-stimulusdifferential as well as target and distracter differential measurementsof ERP time domain components at multiple regions of the brain aredetermined (DERP). Event related time-frequency analysis of thedifferential response to assess the attention, emotion and memoryretention (DERPSPs) across multiple frequency bands including but notlimited to theta, alpha, beta, gamma and high gamma is performed. Inparticular embodiments, single trial and/or averaged DERP and/or DERPSPscan be used to enhance the resonance measure and determine priminglevels for various products and services.

A variety of stimulus materials such as entertainment and marketingmaterials, games, media, performances, sensory experiences, etc. can beanalyzed. Stimulus materials may involve audio, visual, tactile,olfactory, taste, etc. According to various embodiments, enhancedneuro-response data is generated using a data analyzer that performsboth intra-modality measurement enhancements and cross-modalitymeasurement enhancements. According to various embodiments, brainactivity is measured not just to determine the regions of activity, butto determine interactions and types of interactions between variousregions. The techniques and mechanisms of the present inventionrecognize that interactions between neural regions support orchestratedand organized behavior. Attention, emotion, memory, and other abilitiesare not merely based on one part of the brain but instead rely onnetwork interactions between brain regions.

The techniques and mechanisms of the present invention further recognizethat different frequency bands used for multi-regional communication canbe indicative of the effectiveness of stimuli. In particularembodiments, evaluations are calibrated to each subject and synchronizedacross subjects. In particular embodiments, templates are created forsubjects to create a baseline for measuring pre and post stimulusdifferentials. According to various embodiments, stimulus generators areintelligent and adaptively modify specific parameters such as exposurelength and duration for each subject being analyzed.

FIG. 1 illustrates one example of a system for evaluating stimulusmaterials including performing mirror neuron system analysis by usingcentral nervous system, autonomic nervous system, and/or effectormeasures. According to various embodiments, the mirror neuron systemanalysis system includes a stimulus presentation device 101. Inparticular embodiments, the stimulus presentation device 101 is merely adisplay, monitor, screen, etc., that displays stimulus material to auser. The stimulus material may be a media clip, a game, an offer, aperformance, a movie, an audio presentation, and may even involveparticular tastes, smells, textures and/or sounds. According to variousembodiments, the stimulus materials includes a human-like entity such asa person, face, arm, etc., performing an action such as frowning,lifting, running, purchasing, grabbing, etc. The stimuli can involve avariety of senses and occur with or without human supervision.Continuous and discrete modes are supported. According to variousembodiments, the stimulus presentation device 101 also has protocolgeneration capability to allow intelligent customization of stimuli.

According to various embodiments, stimulus presentation device 101 couldinclude devices such as televisions, cable consoles, computers andmonitors, projection systems, display devices, speakers, tactilesurfaces, etc., for presenting the stimuli including but not limited toadvertising and entertainment from different networks, local networks,cable channels, syndicated sources, websites, internet contentaggregators, portals, service providers, etc.

According to various embodiments, the subjects 103 are connected to datacollection devices 105. The data collection devices 105 may include avariety of neuro-response measurement mechanisms including neurologicaland neurophysiological measurements systems such as EEG, EOG, MEG, EKG,pupillary dilation, eye tracking, facial emotion encoding, and reactiontime devices, etc. According to various embodiments, neuro-response dataincludes central nervous system, autonomic nervous system, and effectordata. In particular embodiments, the data collection devices 105 includeEEG 111, EOG 113, and fMRI 115. In some instances, only a single datacollection device such as EEG is used. Data collection may proceed withor without human supervision. According to various embodiments, EEG datais collected from electrodes placed near the inferior frontal lobe andthe posterior parietal lobe before and after a subject is present withmaterial showing human activity.

The data collection device 105 collects neuro-response data frommultiple sources. This includes a combination of devices such as centralnervous system sources (EEG), autonomic nervous system sources (GSR,EKG, pupillary dilation), and effector sources (EOG, eye tracking,facial emotion encoding, reaction time). In particular embodiments, datacollected is digitally sampled and stored for later analysis. Inparticular embodiments, the data collected could be analyzed inreal-time. According to particular embodiments, the digital samplingrates are adaptively chosen based on the neurophysiological andneurological data being measured.

In one particular embodiment, the mirror neuron system analysis systemincludes EEG 111 measurements made using scalp level electrodes, EOG 113measurements made using shielded electrodes to track eye data, fMRI 115measurements performed using a differential measurement system, a facialmuscular measurement through shielded electrodes placed at specificlocations on the face, and a facial affect graphic and video analyzeradaptively derived for each individual.

In particular embodiments, the data collection devices are clocksynchronized with a stimulus presentation device 101. In particularembodiments, the data collection devices 105 also include a conditionevaluation subsystem that provides auto triggers, alerts and statusmonitoring and visualization components that continuously monitor thestatus of the subject, data being collected, and the data collectioninstruments. The condition evaluation subsystem may also present visualalerts and automatically trigger remedial actions. According to variousembodiments, the data collection devices include mechanisms for not onlymonitoring subject neuro-response to stimulus materials, but alsoinclude mechanisms for identifying and monitoring the stimulusmaterials. For example, data collection devices 105 may be synchronizedwith a set-top box to monitor channel changes. In other examples, datacollection devices 105 may be directionally synchronized to monitor whena subject is no longer paying attention to stimulus material. In stillother examples, the data collection devices 105 may receive and storestimulus material generally being viewed by the subject, whether thestimulus is a program, a commercial, a game, or a scene outside awindow. The data collected allows analysis of neuro-response informationand correlation of the information to actual stimulus material and notmere subject distractions.

According to various embodiments, the mirror neuron system analysissystem also includes a data cleanser device 121. In particularembodiments, the data cleanser device 121 filters the collected data toremove noise, artifacts, and other irrelevant data using fixed andadaptive filtering, weighted averaging, advanced component extraction(like PCA, ICA), vector and component separation methods, etc. Thisdevice cleanses the data by removing both exogenous noise (where thesource is outside the physiology of the subject, e.g. a phone ringingwhile a subject is viewing a video) and endogenous artifacts (where thesource could be neurophysiological, e.g. muscle movements, eye blinks,etc.).

The artifact removal subsystem includes mechanisms to selectivelyisolate and review the response data and identify epochs with timedomain and/or frequency domain attributes that correspond to artifactssuch as line frequency, eye blinks, and muscle movements. The artifactremoval subsystem then cleanses the artifacts by either omitting theseepochs, or by replacing these epoch data with an estimate based on theother clean data (for example, an EEG nearest neighbor weightedaveraging approach).

According to various embodiments, the data cleanser device 121 isimplemented using hardware, firmware, and/or software. It should benoted that although a data cleanser device 121 is shown located after adata collection device 105, the data cleanser device 121 like othercomponents may have a location and functionality that varies based onsystem implementation. For example, some systems may not use anyautomated data cleanser device whatsoever while in other systems, datacleanser devices may be integrated into individual data collectiondevices.

In particular embodiments, a survey and interview system collects andintegrates user survey and interview responses to combine withneuro-response data to more effectively select content for delivery.According to various embodiments, the survey and interview systemobtains information about user characteristics such as age, gender,income level, location, interests, buying preferences, hobbies, etc. Thesurvey and interview system can also be used to obtain user responsesabout particular pieces of stimulus material.

According to various embodiments, the mirror neuron system analysissystem includes a mirror neuron system data analyzer 123 associated withthe data cleanser 121. The data analyzer 123 uses a variety ofmechanisms to analyze underlying data in the system to determine mirrorneuron system activity. According to various embodiments, the mirrorneuron data analyzer 123 measures mu, beta, and gamma rhythms from scalplevel electrodes placed near the inferior frontal lobe and the posteriorparietal lobe. Increases in gamma rhythms have been determined tocorrespond to significant mirror neuron system activity. Suppression ofmu and beta rhythms have been determined to correspond to lack of mirrorneuron system activity. The mirror neuron system data analyzer may alsoanalyze other data to obtain an aggregate measure of stimuluseffectiveness.

According to various embodiments, neurological and neuro-physiologicalsignatures are measured using time domain analyses and frequency domainanalyses. Such analyses use parameters that are common acrossindividuals as well as parameters that are unique to each individual.The analyses could also include statistical parameter extraction andfuzzy logic based attribute estimation from both the time and frequencycomponents of the synthesized response.

In some examples, statistical parameters used in a blended effectivenessestimate include evaluations of skew, peaks, first and second moments,distribution, as well as fuzzy estimates of attention, emotionalengagement and memory retention responses.

According to various embodiments, the mirror neuron system data analyzer123 may include an intra-modality response synthesizer and across-modality response synthesizer. In particular embodiments, theintra-modality response synthesizer is configured to customize andextract the independent neurological and neurophysiological parametersfor each individual in each modality and blend the estimates within amodality analytically to elicit an enhanced response to the presentedstimuli. In particular embodiments, the intra-modality responsesynthesizer also aggregates data from different subjects in a dataset.

According to various embodiments, the cross-modality responsesynthesizer or fusion device blends different intra-modality responses,including raw signals and signals output. The combination of signalsenhances the measures of effectiveness within a modality. Thecross-modality response fusion device can also aggregate data fromdifferent subjects in a dataset.

According to various embodiments, the mirror neuron data analyzer 123also includes a composite enhanced effectiveness estimator (CEEE) thatcombines the enhanced responses and estimates from each modality toprovide a blended estimate of the effectiveness. In particularembodiments, blended estimates are provided for each exposure of asubject to stimulus materials. The blended estimates are evaluated overtime to assess resonance characteristics. According to variousembodiments, numerical values are assigned to each blended estimate. Thenumerical values may correspond to the intensity of neuro-responsemeasurements, the significance of peaks, the change between peaks, etc.Higher numerical values may correspond to higher significance inneuro-response intensity. Lower numerical values may correspond to lowersignificance or even insignificant neuro-response activity. In otherexamples, multiple values are assigned to each blended estimate. Instill other examples, blended estimates of neuro-response significanceare graphically represented to show changes after repeated exposure.

According to various embodiments, a mirror neuron data analyzer 123passes data to a resonance estimator that assesses and extractsresonance patterns. In particular embodiments, the resonance estimatordetermines entity positions in various stimulus segments and matchesposition information with eye tracking paths while correlating saccadeswith neural assessments of attention, memory retention, and emotionalengagement. In particular embodiments, the resonance estimator storesdata in the priming repository system. As with a variety of thecomponents in the system, various repositories can be co-located withthe rest of the system and the user, or could be implemented in remotelocations.

Data from the mirror neuron data analyzer 123 is used to generate apropensity to act index 125. According to various embodiments, thepropensity to act index 125 is associated with an individuals propensityto imitate, learn, or perform observed actions done by another. In someexamples, the propensity to act index 125 is a calibrated measure ofgamma rhythms divided by either mu or beta rhythms. In particularembodiments, the index is normalized based on demographiccharacteristics such as gender.

FIG. 2 illustrates examples of data models that may be user in a mirrorneuron system analysis system. According to various embodiments, astimulus attributes data model 201 includes a channel 203, media type205, time span 207, audience 209, and demographic information 211. Astimulus purpose data model 213 may include intents 215 and objectives217. According to various embodiments, stimulus purpose data model 213also includes spatial and temporal information 219 about entities andemerging relationships between entities.

According to various embodiments, another stimulus attributes data model221 includes creation attributes 223, ownership attributes 225,broadcast attributes 227, and statistical, demographic and/or surveybased identifiers 229 for automatically integrating theneuro-physiological and neuro-behavioral response with other attributesand meta-information associated with the stimulus.

According to various embodiments, a stimulus priming data model 231includes fields for identifying advertisement breaks 233 and scenes 235that can be associated with various priming levels 237 and audienceresonance measurements 239. In particular embodiments, the data model231 provides temporal and spatial information for ads, scenes, events,locations, etc. that may be associated with priming levels and audienceresonance measurements. In some examples, priming levels for a varietyof products, services, offerings, etc. are correlated with temporal andspatial information in source material such as a movie, billboard,advertisement, commercial, store shelf, etc. In some examples, the datamodel associates with each second of a show a set of meta-tags forpre-break content indicating categories of products and services thatare primed. The level of priming associated with each category ofproduct or service at various insertions points may also be provided.Audience resonance measurements and maximal audience resonancemeasurements for various scenes and advertisement breaks may bemaintained and correlated with sets of products, services, offerings,etc.

The priming and resonance information may be used to select stimuluscontent suited for particular levels of priming and resonance.

FIG. 3 illustrates examples of data models that can be used for storageof information associated with tracking and measurement of resonance.According to various embodiments, a dataset data model 301 includes anexperiment name 303 and/or identifier, client attributes 305, a subjectpool 307, logistics information 309 such as the location, date, and timeof testing, and stimulus material 311 including stimulus materialattributes.

In particular embodiments, a subject attribute data model 315 includes asubject name 317 and/or identifier, contact information 321, anddemographic attributes 319 that may be useful for review of neurologicaland neuro-physiological data. Some examples of pertinent demographicattributes include marriage status, employment status, occupation,household income, household size and composition, ethnicity, geographiclocation, sex, race. Other fields that may be included in data model 315include subject preferences 323 such as shopping preferences,entertainment preferences, and financial preferences. Shoppingpreferences include favorite stores, shopping frequency, categoriesshopped, favorite brands. Entertainment preferences includenetwork/cable/satellite access capabilities, favorite shows, favoritegenres, and favorite actors. Financial preferences include favoriteinsurance companies, preferred investment practices, bankingpreferences, and favorite online financial instruments. A variety ofproduct and service attributes and preferences may also be included. Avariety of subject attributes may be included in a subject attributesdata model 315 and data models may be preset or custom generated to suitparticular purposes.

According to various embodiments, data models for neuro-feedbackassociation 325 identify experimental protocols 327, modalities included329 such as EEG, EOG, GSR, surveys conducted, and experiment designparameters 333 such as segments and segment attributes. Other fields mayinclude experiment presentation scripts, segment length, segment detailslike stimulus material used, inter-subject variations, intra-subjectvariations, instructions, presentation order, survey questions used,etc. Other data models may include a data collection data model 337.According to various embodiments, the data collection data model 337includes recording attributes 339 such as station and locationidentifiers, the data and time of recording, and operator details. Inparticular embodiments, equipment attributes 341 include an amplifieridentifier and a sensor identifier.

Modalities recorded 343 may include modality specific attributes likeEEG cap layout, active channels, sampling frequency, and filters used.EOG specific attributes include the number and type of sensors used,location of sensors applied, etc. Eye tracking specific attributesinclude the type of tracker used, data recording frequency, data beingrecorded, recording format, etc. According to various embodiments, datastorage attributes 345 include file storage conventions (format, namingconvention, dating convention), storage location, archival attributes,expiry attributes, etc.

A preset query data model 349 includes a query name 351 and/oridentifier, an accessed data collection 353 such as data segmentsinvolved (models, databases/cubes, tables, etc.), access securityattributes 355 included who has what type of access, and refreshattributes 357 such as the expiry of the query, refresh frequency, etc.Other fields such as push-pull preferences can also be included toidentify an auto push reporting driver or a user driven report retrievalsystem.

FIG. 4 illustrates examples of queries that can be performed to obtaindata associated with mirror neuron system analysis. According to variousembodiments, queries are defined from general or customized scriptinglanguages and constructs, visual mechanisms, a library of presetqueries, diagnostic querying including drill-down diagnostics, andeliciting what if scenarios. According to various embodiments, subjectattributes queries 415 may be configured to obtain data from aneuro-informatics repository using a location 417 or geographicinformation, session information 421 such as testing times and dates,and demographic attributes 419. Demographics attributes includehousehold income, household size and status, education level, age ofkids, etc.

Other queries may retrieve stimulus material based on shoppingpreferences of subject participants, countenance, physiologicalassessment, completion status. For example, a user may query for dataassociated with product categories, products shopped, shops frequented,subject eye correction status, color blindness, subject state, signalstrength of measured responses, alpha frequency band ringers, musclemovement assessments, segments completed, etc. Experimental design basedqueries 425 may obtain data from a neuro-informatics repository based onexperiment protocols 427, product category 429, surveys included 431,and stimulus provided 433. Other fields that may be used include thenumber of protocol repetitions used, combination of protocols used, andusage configuration of surveys.

Client and industry based queries may obtain data based on the types ofindustries included in testing, specific categories tested, clientcompanies involved, and brands being tested. Response assessment basedqueries 437 may include attention scores 439, emotion scores, 441,retention scores 443, and effectiveness scores 445. Such queries mayobtain materials that elicited particular scores. In particularembodiments, propensity queries 447 may include aggregate propensity toact 449 queries, propensity to reach 451, learning index 453, andempathy index 455 queries.

Response measure profile based queries may use mean measure thresholds,variance measures, number of peaks detected, etc. Group response queriesmay include group statistics like mean, variance, kurtosis, p-value,etc., group size, and outlier assessment measures. Still other queriesmay involve testing attributes like test location, time period, testrepetition count, test station, and test operator fields. A variety oftypes and combinations of types of queries can be used to efficientlyextract data.

FIG. 5 illustrates examples of reports that can be generated. Accordingto various embodiments, client assessment summary reports 501 includeeffectiveness measures 503, component assessment measures 505, andresonance measures 507. Effectiveness assessment measures includecomposite assessment measure(s), industry/category/client specificplacement (percentile, ranking, etc.), actionable grouping assessmentsuch as removing material, modifying segments, or fine tuning specificelements, etc, and the evolution of the effectiveness profile over time.In particular embodiments, component assessment reports includecomponent assessment measures like attention, emotional engagementscores, percentile placement, ranking, etc. Component profile measuresinclude time based evolution of the component measures and profilestatistical assessments. According to various embodiments, reportsinclude the number of times material is assessed, attributes of themultiple presentations used, evolution of the response assessmentmeasures over the multiple presentations, and usage recommendations.

According to various embodiments, client cumulative reports 511 includemedia grouped reporting 513 of all stimulus assessed, campaign groupedreporting 515 of stimulus assessed, and time/location grouped reporting517 of stimulus assessed. According to various embodiments, industrycumulative and syndicated reports 521 include aggregate assessmentresponses measures 523, top performer lists 525, bottom performer lists527, outliers 529, and trend reporting 531. In particular embodiments,tracking and reporting includes specific products, categories,companies, brands. According to various embodiments, propensity reports533 are also generated. Propensity reports may include propensity to act535, propensity to reach 537, learning index 539, and empathy index 541reports.

FIG. 6 illustrates one example of mirror neuron system analysis. At 601,stimulus material is provided to multiple subjects. According to variousembodiments, stimulus includes streaming video depicting a non-humanlike entity such as a stick figure, machine, or object performing anaction. In particular embodiments, subjects view stimulus in their ownhomes in group or individual settings. In some examples, verbal andwritten responses are collected for use without neuro-responsemeasurements. In other examples, verbal and written responses arecorrelated with neuro-response measurements. At 603, subjectneuro-response measurements are collected using a variety of modalities,such as EEG, MEG, etc. At 605, data is passed through a data cleanser toremove noise and artifacts that may make data more difficult tointerpret. According to various embodiments, the data cleanser removesEEG electrical activity associated with blinking and otherendogenous/exogenous artifacts.

According to various embodiments, data analysis is performed to detectmu and/or beta rhythm suppression at 607, particularly in areasassociated with the mirror neuron system. Data is also analyzed todetect increases in gamma rhythms at 609, again particularly in areasassociated with the mirror neuron system. At 611, a mirror neuron systembaseline is generated. Mirror neuron system baselines may be generatedon an individual, subgroup, and group basis. At 613, integrated data issent to a mirror neuron system analyzer repository 619. The integrateddata may include subject responses and resulting behavior informationfrom the subject. The data sent to the mirror neuron system analyzerrepository 619 may be used to provide a baseline for further individual,subgroup, and group measurements of mirror neuron system activitydetected in subjects exposed to stimulus material.

According to various embodiments, neuro-response data is analyzed to notonly measure mirror neuron system activity in response to stimulus butto also determine other measures of stimulus effectiveness. A variety ofmechanisms can be used to perform data analysis and to analyze stimulusmaterial effectiveness. EEG response data can be synthesized to providean enhanced assessment of effectiveness. According to variousembodiments, EEG measures electrical activity resulting from thousandsof simultaneous neural processes associated with different portions ofthe brain. EEG data can be classified in various bands. According tovarious embodiments, brainwave frequencies include delta, theta, alpha,beta, and gamma frequency ranges. Delta waves are classified as thoseless than 4 Hz and are prominent during deep sleep. Theta waves havefrequencies between 3.5 to 7.5 Hz and are associated with memories,attention, emotions, and sensations. Theta waves are typically prominentduring states of internal focus.

Alpha frequencies reside between 7.5 and 13 Hz and typically peak around10 Hz. Alpha waves are prominent during states of relaxation. Beta waveshave a frequency range between 14 and 30 Hz. Beta waves are prominentduring states of motor control, long range synchronization between brainareas, analytical problem solving, judgment, and decision making. Gammawaves occur between 30 and 60 Hz and are involved in binding ofdifferent populations of neurons together into a network for the purposeof carrying out a certain cognitive or motor function, as well as inattention and memory. Because the skull and dermal layers attenuatewaves in this frequency range, brain waves above 75-80 Hz are difficultto detect and are often not used for stimuli response assessment.

However, the techniques and mechanisms of the present inventionrecognize that analyzing high gamma band (kappa-band: Above 60 Hz)measurements, in addition to theta, alpha, beta, and low gamma bandmeasurements, enhances neurological attention, emotional engagement andretention component estimates. In particular embodiments, EEGmeasurements including difficult to detect high gamma or kappa bandmeasurements are obtained, enhanced, and evaluated. Subject and taskspecific signature sub-bands in the theta, alpha, beta, gamma and kappabands are identified to provide enhanced response estimates. Accordingto various embodiments, high gamma waves (kappa-band) above 80 Hz(typically detectable with sub-cranial EEG and/ormagnetoencephalograophy) can be used in inverse model-based enhancementof the frequency responses to the stimuli.

Various embodiments of the present invention recognize that particularsub-bands within each frequency range have particular prominence duringcertain activities. A subset of the frequencies in a particular band isreferred to herein as a sub-band. For example, a sub-band may includethe 40-45 Hz range within the gamma band. In particular embodiments,multiple sub-bands within the different bands are selected whileremaining frequencies are band pass filtered. In particular embodiments,multiple sub-band responses may be enhanced, while the remainingfrequency responses may be attenuated.

An information theory based band-weighting model is used for adaptiveextraction of selective dataset specific, subject specific, taskspecific bands to enhance the effectiveness measure. Adaptive extractionmay be performed using fuzzy scaling. Stimuli can be presented andenhanced measurements determined multiple times to determine thevariation profiles across multiple presentations. Determining variousprofiles provides an enhanced assessment of the primary responses aswell as the longevity (wear-out) of the marketing and entertainmentstimuli. The synchronous response of multiple individuals to stimulipresented in concert is measured to determine an enhanced across subjectsynchrony measure of effectiveness. According to various embodiments,the synchronous response may be determined for multiple subjectsresiding in separate locations or for multiple subjects residing in thesame location.

Although a variety of synthesis mechanisms are described, it should berecognized that any number of mechanisms can be applied—in sequence orin parallel with or without interaction between the mechanisms.

Although intra-modality synthesis mechanisms provide enhancedsignificance data, additional cross-modality synthesis mechanisms canalso be applied. A variety of mechanisms such as EEG, Eye Tracking, GSR,EOG, and facial emotion encoding are connected to a cross-modalitysynthesis mechanism. Other mechanisms as well as variations andenhancements on existing mechanisms may also be included. According tovarious embodiments, data from a specific modality can be enhanced usingdata from one or more other modalities. In particular embodiments, EEGtypically makes frequency measurements in different bands like alpha,beta and gamma to provide estimates of significance. However, thetechniques of the present invention recognize that significance measurescan be enhanced further using information from other modalities.

For example, facial emotion encoding measures can be used to enhance thevalence of the EEG emotional engagement measure. EOG and eye trackingsaccadic measures of object entities can be used to enhance the EEGestimates of significance including but not limited to attention,emotional engagement, and memory retention. According to variousembodiments, a cross-modality synthesis mechanism performs time andphase shifting of data to allow data from different modalities to align.In some examples, it is recognized that an EEG response will often occurhundreds of milliseconds before a facial emotion measurement changes.Correlations can be drawn and time and phase shifts made on anindividual as well as a group basis. In other examples, saccadic eyemovements may be determined as occurring before and after particular EEGresponses. According to various embodiments, time corrected GSR measuresare used to scale and enhance the EEG estimates of significanceincluding attention, emotional engagement and memory retention measures.

Evidence of the occurrence or non-occurrence of specific time domaindifference event-related potential components (like the DERP) inspecific regions correlates with subject responsiveness to specificstimulus. According to various embodiments, ERP measures are enhancedusing EEG time-frequency measures (ERPSP) in response to thepresentation of the marketing and entertainment stimuli. Specificportions are extracted and isolated to identify ERP, DERP and ERPSPanalyses to perform. In particular embodiments, an EEG frequencyestimation of attention, emotion and memory retention (ERPSP) is used asa co-factor in enhancing the ERP, DERP and time-domain responseanalysis.

EOG measures saccades to determine the presence of attention to specificobjects of stimulus. Eye tracking measures the subject's gaze path,location and dwell on specific objects of stimulus. According to variousembodiments, EOG and eye tracking is enhanced by measuring the presenceof lambda waves (a neurophysiological index of saccade effectiveness) inthe ongoing EEG in the occipital and extra striate regions, triggered bythe slope of saccade-onset to estimate the significance of the EOG andeye tracking measures. In particular embodiments, specific EEGsignatures of activity such as slow potential shifts and measures ofcoherence in time-frequency responses at the Frontal Eye Field (FEF)regions that preceded saccade-onset are measured to enhance theeffectiveness of the saccadic activity data.

According to various embodiments, facial emotion encoding uses templatesgenerated by measuring facial muscle positions and movements ofindividuals expressing various emotions prior to the testing session.These individual specific facial emotion encoding templates are matchedwith the individual responses to identify subject emotional response. Inparticular embodiments, these facial emotion encoding measurements areenhanced by evaluating inter-hemispherical asymmetries in EEG responsesin specific frequency bands and measuring frequency band interactions.The techniques of the present invention recognize that not only areparticular frequency bands significant in EEG responses, but particularfrequency bands used for communication between particular areas of thebrain are significant. Consequently, these EEG responses enhance theEMG, graphic and video based facial emotion identification.

In some examples, post-stimulus versus pre-stimulus differentialmeasurements of ERP time domain components in multiple regions of thebrain (DERP) are measured at multiple regions of the brain. Thedifferential measures give a mechanism for eliciting responsesattributable to the stimulus. For example the messaging responseattributable to an advertisement or the brand response attributable tomultiple brands is determined using pre-resonance and post-resonanceestimates

Target versus distracter stimulus differential responses are determinedfor different regions of the brain (DERP). Event related time-frequencyanalysis of the differential response (DERPSPs) are used to assess theattention, emotion and memory retention measures across multiplefrequency bands. According to various embodiments, the multiplefrequency bands include theta, alpha, beta, gamma and high gamma orkappa.

FIG. 7 illustrates an example of a technique for mirror neuron systemanalysis. At 701, stimulus material is provided to multiple subjects.According to various embodiments, stimulus includes streaming videodepicting a human like entity such as a human hand, face, semi-realisticanimation, etc., performing an action. In particular embodiments,subjects view stimulus in their own homes in group or individualsettings. In some examples, verbal and written responses are collectedfor use without neuro-response measurements. In other examples, verbaland written responses are correlated with neuro-response measurements.At 703, subject neuro-response measurements are collected using avariety of modalities, such as EEG, MEG, etc. At 705, data is passedthrough a data cleanser to remove noise and artifacts that may make datamore difficult to interpret. According to various embodiments, the datacleanser removes EEG electrical activity associated with blinking andother endogenous/exogenous artifacts.

According to various embodiments, data analysis is performed to detectmu and/or beta rhythm suppression at 707, particularly in areasassociated with the mirror neuron system. Data is also analyzed todetect increases in gamma rhythms at 709, again particularly in areasassociated with the mirror neuron system. At 711, a mirror neuron systembaseline along with gamma and beta/mu rhythms can be used to generate apropensity to act index. According to various embodiments, a propensityto act index corresponds to gamma rhythms divided by either beta or murhythms. In some examples, survey responses and resulting behaviorinformation is integrated at 713. It should be noted that propensity toreach, learning index, and empathy index measures can also be generatedusing gamma, beta, mu, and baseline measurements along with resultingbehavior and survey information. At 717, multiple trials are performedto enhance measurements. At 719, data is sent to a mirror neuron systemanalyzer repository.

According to various embodiments, various mechanisms such as the datacollection mechanisms, the intra-modality synthesis mechanisms,cross-modality synthesis mechanisms, etc. are implemented on multipledevices. However, it is also possible that the various mechanisms beimplemented in hardware, firmware, and/or software in a single system.FIG. 8 provides one example of a system that can be used to implementone or more mechanisms. For example, the system shown in FIG. 8 may beused to implement a resonance measurement system.

According to particular example embodiments, a system 800 suitable forimplementing particular embodiments of the present invention includes aprocessor 801, a memory 803, an interface 811, and a bus 815 (e.g., aPCI bus). When acting under the control of appropriate software orfirmware, the processor 801 is responsible for such tasks such aspattern generation. Various specially configured devices can also beused in place of a processor 801 or in addition to processor 801. Thecomplete implementation can also be done in custom hardware. Theinterface 811 is typically configured to send and receive data packetsor data segments over a network. Particular examples of interfaces thedevice supports include host bus adapter (HBA) interfaces, Ethernetinterfaces, frame relay interfaces, cable interfaces, DSL interfaces,token ring interfaces, and the like.

According to particular example embodiments, the system 800 uses memory803 to store data, algorithms and program instructions. The programinstructions may control the operation of an operating system and/or oneor more applications, for example. The memory or memories may also beconfigured to store received data and process received data.

Because such information and program instructions may be employed toimplement the systems/methods described herein, the present inventionrelates to tangible, machine readable media that include programinstructions, state information, etc. for performing various operationsdescribed herein. Examples of machine-readable media include, but arenot limited to, magnetic media such as hard disks, floppy disks, andmagnetic tape; optical media such as CD-ROM disks and DVDs;magneto-optical media such as optical disks; and hardware devices thatare specially configured to store and perform program instructions, suchas read-only memory devices (ROM) and random access memory (RAM).Examples of program instructions include both machine code, such asproduced by a compiler, and files containing higher level code that maybe executed by the computer using an interpreter.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. Therefore, the present embodiments are to be consideredas illustrative and not restrictive and the invention is not to belimited to the details given herein, but may be modified within thescope and equivalents of the appended claims.

What is claimed is:
 1. A method, comprising: analyzing, using aprocessor, neuro-response data from a subject exposed to first stimulusmaterial, wherein the neuro-response data includes data obtained fromareas of a brain of the subject associated with a mirror neuron system,and the neuro-response data includes gamma band data and mu band data;identifying at least one of (1) an increase in mirror neuron activitybased on an increase in gamma band data and a decrease in mu band dataor (2) a decrease in mirror neuron activity based on a decrease in gammaband data and an increase in mu band data; and generating, using theprocessor, a propensity to act index indicating at least one of (a) thatthe subject is likely to take an action based on the increase in themirror neuron activity or (b) that the subject is not likely to take theaction based on the decrease in the mirror neuron activity.
 2. Themethod of claim 1, wherein the gamma band data comprises gamma rhythms.3. The method of claim 1, wherein the neuro-response data includes betaband data and the propensity to act index is further based on a ratio ofthe gamma band data to the beta band data, and the beta band datacomprises beta rhythms.
 4. The method of claim 1, wherein the mu banddata comprises mu rhythms.
 5. The method of claim 1, wherein thepropensity to act is further based on a ratio of the gamma band data tothe mu band data.
 6. The method of claim 1, wherein the neuron-responsedata is obtained using electroencephalography.
 7. The method of claim 1,wherein the neuro-response data is obtained usingmagnetoencephalography.
 8. The method of claim 1 further comprisinggenerating a baseline by analyzing second neuro-response data gatheredfrom the subject while exposed to second stimulus material before thesubject is exposed to the first stimulus material.
 9. The method ofclaim 1, wherein the propensity to act index is calibrated based on ademographic group.
 10. The method of claim 9, wherein the propensity toact index is calibrated based on a gender.
 11. The method of claim 1further comprising generating a propensity to reach index based on theneuro-response data.
 12. The method of claim 1 further comprisinggenerating a learning index based on the neuro-response data.
 13. Themethod of claim 1 further comprising generating an empathy index basedon the neuro-response data.
 14. A system, comprising: a data collectorto obtain neuro-response data from a subject exposed to first stimulusmaterial, wherein the neuro-response data includes data obtained fromareas of a brain of the subject associated with a mirror neuron system,the neuro-response data including gamma band data and mu band data; anda data analyzer to: identify at least one of (1) an increase in mirrorneuron activity based on (a) an increase in gamma band data and (b) adecrease in mu band data or (2) a decrease in mirror neuron activitybased on (a) a decrease in gamma band data and (b) an increase in muband data; and generate a propensity to act index indicating at leastone of (1) that the subject is likely to take an action based on theincrease in the mirror neuron activity or (2) that the subject is notlikely to take the action based on the decrease in the mirror neuronactivity.
 15. The system of claim 14, wherein the gamma band datacomprises gamma rhythms.
 16. The system of claim 14, wherein theneuro-response data includes beta band data and the data analyzer is togenerate the propensity to act index based on a ratio of the gamma banddata to the beta band data, the beta band data comprising beta rhythms.17. The system of claim 14, wherein the mu band data comprises murhythms.
 18. The system of claim 14, wherein the data analyzer is togenerate the propensity to act index based on a ratio of the gamma banddata to the mu band data.
 19. The system of claim 14, wherein the datacollector is to obtain the neuron-response data usingelectroencephalography.
 20. The system of claim 14, wherein the dataanalyzer is to generate a baseline by analyzing second neuro-responsedata gathered from the subject while exposed to second stimulus materialbefore the subject is exposed to the first stimulus material.
 21. Thesystem of claim 14, wherein the data analyzer is to calibrate thepropensity to act index based on a demographic group.
 22. The system ofclaim 21, wherein the data analyzer is to calibrate the propensity toact index based on a gender.
 23. The system of claim 14, wherein thedata analyzer is to generate a propensity to reach index based on theneuro-response data.
 24. The system of claim 14, wherein the dataanalyzer is to generate a learning index based on the neuro-responsedata.
 25. The system of claim 14, wherein the data analyzer is togenerate an empathy index based on the neuro-response data.
 26. Atangible machine readable storage device or storage disc comprisinginstructions which, when executed, cause a machine to at least: accessneuro-response data from a subject exposed to stimulus material, whereinthe neuro-response data includes data obtained from areas of a brain ofthe subject associated with a mirror neuron system, the neuro-responsedata including gamma band data and mu band data; identify at least oneof (1) an increase in mirror neuron activity based on (a) an increase ingamma band data and (b) a decrease in mu band data or (2) a decrease inmirror neuron activity based on (a) a decrease in gamma band data and(b) an increase in mu band data; and generate a propensity to act indexindicating at least one of (1) that the subject is likely to take anaction based on the increase in the mirror neuron activity or (2) thatthe subject is not likely to take the action based on the decrease inthe mirror neuron activity.